A global optimal scheduling algorithm for multiprocessor low-power platforms

Funk, Shelby; Berten, Vandy; Ho, Chiahsun; Goossens, Joël

doi:10.1145/2392987.2392996

Cited by 11 publications

(6 citation statements)

References 25 publications

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“…Note that the tasks that have been split migrate between the two assigned processors. The work of [14] was extended in [16], [17] by incorporating a DVFS scheme to reduce power consumption.…”

Section: Related Workmentioning

confidence: 99%

“…• If the active power function P active is convex and the speed level sets are closed intervals, compute a solution to (15). If there is more than one intercluster partitioning task, then the (finite) range of the optimal speed profile should be used to define and compute a solution to (16) with at most one intercluster partitioning task. This process is concluded with Algorithm 1.…”

Section: Constant or Time-varying Speed?mentioning

confidence: 99%

“…However, the algorithms that are based on the fairness notion [13], [14], [16]- [19] are feasibility optimal, but have hardly been applied in a real system, since they suffer from high scheduling overheads, i.e. task preemptions and migrations.…”

Section: Related Workmentioning

confidence: 99%

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Energy-efficient real-time scheduling for two-type heterogeneous multiprocessors

Thammawichai

Kerrigan

2017

Real-Time Syst

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We propose three novel mathematical optimization formulations that solve the same two-type heterogeneous multiprocessor scheduling problem for a real-time taskset with hard constraints. Our formulations are based on a global scheduling scheme and a fluid model. The first formulation is a mixed-integer nonlinear program, since the scheduling problem is intuitively considered as an assignment problem. However, by changing the scheduling problem to first determine a task workload partition and then to find the execution order of all tasks, the computation time can be significantly reduced. Specifically, the workload partitioning problem can be formulated as a continuous nonlinear program for a system with continuous operating frequency, and as a continuous linear program for a practical system with a discrete speed level set. The latter problem can therefore be solved by an interior point method to any accuracy in polynomial time. The task ordering problem can be solved by an algorithm with a complexity that is linear in the total number of tasks. The work is evaluated against existing global energy/feasibility optimal workload allocation formulations. The results illustrate that our algorithms are both feasibility optimal and energy optimal for both implicit and constrained deadline tasksets. Specifically, our algorithm can achieve up to 40% energy saving for some simulated tasksets with constrained deadlines. The benefit of our formulation compared with existing work is that our algorithms can solve a more general class of scheduling problems due to incorporat-

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Section: Related Workmentioning

confidence: 99%

Section: Constant or Time-varying Speed?mentioning

confidence: 99%

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Energy-efficient real-time scheduling for two-type heterogeneous multiprocessors

Thammawichai

Kerrigan

2017

Real-Time Syst

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“…However, the algorithms that are based on the fairness notion [3]- [5], [7], [9], [10] are schedulability optimal, but have hardly been applied in a real system, since they suffer from high scheduling overheads, i.e. task pre-emptions and migrations.…”

Section: Related Workmentioning

confidence: 99%

Feedback scheduling for energy-efficient real-time homogeneous multiprocessor systems

Thammawichai¹,

Kerrigan

2016

2016 IEEE 55th Conference on Decision and Control (CDC)

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Abstract-Real-time scheduling algorithms proposed in the literature are often based on worst-case estimates of task parameters. The performance of an open-loop scheme can be degraded significantly if there are uncertainties in task parameters, such as the execution times of the tasks. Therefore, to cope with such a situation, a closed-loop scheme, where feedback is exploited to adjust the system parameters, can be applied. We propose an optimal control framework that takes advantage of feeding back information of finished tasks to solve a real-time multiprocessor scheduling problem with uncertainty in task execution times, with the objective of minimizing the total energy consumption. Specifically, we propose a linear programming based algorithm to solve a workload partitioning problem and adopt McNaughton's wrap around algorithm to find the task execution order. The simulation results illustrate that our feedback scheduling algorithm can save energy by as much as 40% compared to an open-loop method for two processor models, i.e. a PowerPC 405LP and an XScale processor.

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“…There have been many studies on DVFS on multiprocessor (or multicore) real-time systems [1,[6][7][8][9][10][11][12][13][14][15][16]22,[26][27]. Among them, Han et.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Speed Dynamic Voltage/Frequency Scaling Scheme for Multicore Real-Time Systems

2020

IJETER

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DVFS (dynamic voltage /frequency scaling) is a well-known and prevalent low power technique in processor components. This article proposes a DVFS scheme for multicore real-time systems. The proposed scheme divides the worst-case processor time of a real-time task into multiple sections and associates different speed with each section in increasing order. As a job executes and progresses, its speed increases according to the speed associated with the sections. If a job's actual execution requirement is smaller than its worst-case execution requirement, the job starts and executes at a low speed. The amount of consumed energy is less than the worst case. We integrate and evaluate the scheme with a multicore real-time scheduling. The results show that our multi-speed scheme can save energy consumption by up to 6.99% compared with the individual speed scheme. And we also show that our scheme performs better as the number of sections increases.

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A global optimal scheduling algorithm for multiprocessor low-power platforms

Cited by 11 publications

References 25 publications

Energy-efficient real-time scheduling for two-type heterogeneous multiprocessors

Energy-efficient real-time scheduling for two-type heterogeneous multiprocessors

Feedback scheduling for energy-efficient real-time homogeneous multiprocessor systems

A Multi-Speed Dynamic Voltage/Frequency Scaling Scheme for Multicore Real-Time Systems

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